{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Base Editing (BE) Coverage analysis\n",
    "\n",
    "- This notebook provides a quantification of the capabilities of base editing to model mutations present in the MSK IMPACT dataset.\n",
    "    - Assumptions:\n",
    "        - Using an NGG PAM site for the base editor\n",
    "        - ideal/high efficiency editing window is +4 to +8 (inclusive) in the protospacer\n",
    "        - I look at both adenine and cytosine base editors\n",
    "\n",
    "For more information regarding collection MSK IMPACT methods, etc., see: \n",
    "- https://www.mskcc.org/msk-impact\n",
    "- https://datacatalog.mskcc.org/dataset/10438"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5g/xxjcy2g531n02hnyb6d8qdsr0000gn/T/ipykernel_32865/836307472.py:2: DtypeWarning: Columns (45,48,88) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  impact_data = pd.read_csv(filepath, sep='\\t')\n"
     ]
    }
   ],
   "source": [
    "filepath = '/Volumes/Sam_G_SSD/2020-06-16-MSK-IMPACT_EDITED.txt'\n",
    "impact_data = pd.read_csv(filepath, sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hugo_Symbol</th>\n",
       "      <th>Entrez_Gene_Id</th>\n",
       "      <th>Center</th>\n",
       "      <th>NCBI_Build</th>\n",
       "      <th>Chromosome</th>\n",
       "      <th>Start_Position</th>\n",
       "      <th>End_Position</th>\n",
       "      <th>Strand</th>\n",
       "      <th>Consequence</th>\n",
       "      <th>Variant_Classification</th>\n",
       "      <th>...</th>\n",
       "      <th>VARIANT_CLASS</th>\n",
       "      <th>all_effects</th>\n",
       "      <th>amino_acid_change</th>\n",
       "      <th>cDNA_Change</th>\n",
       "      <th>cDNA_position</th>\n",
       "      <th>cdna_change</th>\n",
       "      <th>comments</th>\n",
       "      <th>n_depth</th>\n",
       "      <th>t_depth</th>\n",
       "      <th>transcript</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BRCA2</td>\n",
       "      <td>675</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>13</td>\n",
       "      <td>32937315</td>\n",
       "      <td>32937315</td>\n",
       "      <td>+</td>\n",
       "      <td>splice_acceptor_variant</td>\n",
       "      <td>Splice_Site</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BRCA2</td>\n",
       "      <td>0</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>37</td>\n",
       "      <td>13</td>\n",
       "      <td>32914437</td>\n",
       "      <td>32914438</td>\n",
       "      <td>+</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MUTYH</td>\n",
       "      <td>4595</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>1</td>\n",
       "      <td>45798475</td>\n",
       "      <td>45798475</td>\n",
       "      <td>+</td>\n",
       "      <td>missense_variant</td>\n",
       "      <td>Missense_Mutation</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BRCA2</td>\n",
       "      <td>675</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>13</td>\n",
       "      <td>32893302</td>\n",
       "      <td>32893302</td>\n",
       "      <td>+</td>\n",
       "      <td>frameshift_variant</td>\n",
       "      <td>Frame_Shift_Ins</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BRCA1</td>\n",
       "      <td>0</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>37</td>\n",
       "      <td>17</td>\n",
       "      <td>41251824</td>\n",
       "      <td>41251825</td>\n",
       "      <td>+</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422817</th>\n",
       "      <td>SMARCA4</td>\n",
       "      <td>6597</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>19</td>\n",
       "      <td>11144132</td>\n",
       "      <td>11144132</td>\n",
       "      <td>+</td>\n",
       "      <td>missense_variant</td>\n",
       "      <td>Missense_Mutation</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422818</th>\n",
       "      <td>BRAF</td>\n",
       "      <td>673</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>7</td>\n",
       "      <td>140453149</td>\n",
       "      <td>140453149</td>\n",
       "      <td>+</td>\n",
       "      <td>missense_variant</td>\n",
       "      <td>Missense_Mutation</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422819</th>\n",
       "      <td>NRAS</td>\n",
       "      <td>4893</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>1</td>\n",
       "      <td>115258747</td>\n",
       "      <td>115258747</td>\n",
       "      <td>+</td>\n",
       "      <td>missense_variant</td>\n",
       "      <td>Missense_Mutation</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422820</th>\n",
       "      <td>TERT</td>\n",
       "      <td>7015</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>5</td>\n",
       "      <td>1295521</td>\n",
       "      <td>1295521</td>\n",
       "      <td>+</td>\n",
       "      <td>upstream_gene_variant</td>\n",
       "      <td>5'Flank</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422821</th>\n",
       "      <td>KRAS</td>\n",
       "      <td>3845</td>\n",
       "      <td>MSKCC</td>\n",
       "      <td>GRCh37</td>\n",
       "      <td>12</td>\n",
       "      <td>25398284</td>\n",
       "      <td>25398284</td>\n",
       "      <td>+</td>\n",
       "      <td>missense_variant</td>\n",
       "      <td>Missense_Mutation</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>422822 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Hugo_Symbol  Entrez_Gene_Id Center NCBI_Build Chromosome  \\\n",
       "0            BRCA2             675  MSKCC     GRCh37         13   \n",
       "1            BRCA2               0  MSKCC         37         13   \n",
       "2            MUTYH            4595  MSKCC     GRCh37          1   \n",
       "3            BRCA2             675  MSKCC     GRCh37         13   \n",
       "4            BRCA1               0  MSKCC         37         17   \n",
       "...            ...             ...    ...        ...        ...   \n",
       "422817     SMARCA4            6597  MSKCC     GRCh37         19   \n",
       "422818        BRAF             673  MSKCC     GRCh37          7   \n",
       "422819        NRAS            4893  MSKCC     GRCh37          1   \n",
       "422820        TERT            7015  MSKCC     GRCh37          5   \n",
       "422821        KRAS            3845  MSKCC     GRCh37         12   \n",
       "\n",
       "        Start_Position  End_Position Strand              Consequence  \\\n",
       "0             32937315      32937315      +  splice_acceptor_variant   \n",
       "1             32914437      32914438      +                      NaN   \n",
       "2             45798475      45798475      +         missense_variant   \n",
       "3             32893302      32893302      +       frameshift_variant   \n",
       "4             41251824      41251825      +                      NaN   \n",
       "...                ...           ...    ...                      ...   \n",
       "422817        11144132      11144132      +         missense_variant   \n",
       "422818       140453149     140453149      +         missense_variant   \n",
       "422819       115258747     115258747      +         missense_variant   \n",
       "422820         1295521       1295521      +    upstream_gene_variant   \n",
       "422821        25398284      25398284      +         missense_variant   \n",
       "\n",
       "       Variant_Classification  ... VARIANT_CLASS all_effects  \\\n",
       "0                 Splice_Site  ...           NaN         NaN   \n",
       "1                         NaN  ...           NaN         NaN   \n",
       "2           Missense_Mutation  ...           NaN         NaN   \n",
       "3             Frame_Shift_Ins  ...           NaN         NaN   \n",
       "4                         NaN  ...           NaN         NaN   \n",
       "...                       ...  ...           ...         ...   \n",
       "422817      Missense_Mutation  ...           NaN         NaN   \n",
       "422818      Missense_Mutation  ...           NaN         NaN   \n",
       "422819      Missense_Mutation  ...           NaN         NaN   \n",
       "422820                5'Flank  ...           NaN         NaN   \n",
       "422821      Missense_Mutation  ...           NaN         NaN   \n",
       "\n",
       "       amino_acid_change cDNA_Change cDNA_position  cdna_change comments  \\\n",
       "0                    NaN         NaN           NaN          NaN      NaN   \n",
       "1                    NaN         NaN           NaN          NaN      NaN   \n",
       "2                    NaN         NaN           NaN          NaN      NaN   \n",
       "3                    NaN         NaN           NaN          NaN      NaN   \n",
       "4                    NaN         NaN           NaN          NaN      NaN   \n",
       "...                  ...         ...           ...          ...      ...   \n",
       "422817               NaN         NaN           NaN          NaN      NaN   \n",
       "422818               NaN         NaN           NaN          NaN      NaN   \n",
       "422819               NaN         NaN           NaN          NaN      NaN   \n",
       "422820               NaN         NaN           NaN          NaN      NaN   \n",
       "422821               NaN         NaN           NaN          NaN      NaN   \n",
       "\n",
       "        n_depth  t_depth  transcript  \n",
       "0           NaN      NaN         NaN  \n",
       "1           NaN      NaN         NaN  \n",
       "2           NaN      NaN         NaN  \n",
       "3           NaN      NaN         NaN  \n",
       "4           NaN      NaN         NaN  \n",
       "...         ...      ...         ...  \n",
       "422817      NaN      NaN         NaN  \n",
       "422818      NaN      NaN         NaN  \n",
       "422819      NaN      NaN         NaN  \n",
       "422820      NaN      NaN         NaN  \n",
       "422821      NaN      NaN         NaN  \n",
       "\n",
       "[422822 rows x 123 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "impact_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 594 unique genes observed\n"
     ]
    }
   ],
   "source": [
    "#list of unique genes tested\n",
    "unique_genes = np.unique(np.asarray(impact_data['Hugo_Symbol']))\n",
    "print('There are ' + str(len(unique_genes)) + ' unique genes observed')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading in reference genome and annotation files\n",
    "\n",
    "- Annotation file generated in Genome Processing notebook\n",
    "- Downloading reference sequence from: https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26/ (assembly GRCh38)\n",
    "- GRCh37: https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.25\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Bio import SeqIO\n",
    "import gzip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['37', 'GRCh37'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#MSK IMPACT dataset uses GrCh37 build\n",
    "np.unique(np.asarray(impact_data['NCBI_Build']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = '/Volumes/Sam_G_SSD/GRCh37/ncbi-genomes-2022-03-17/GCF_000001405.25_GRCh37.p13_genomic.fna.gz'\n",
    "\n",
    "with gzip.open(file, \"rt\") as handle:\n",
    "    records = list(SeqIO.parse(handle, \"fasta\")) #about 4 Gb in  memory\n",
    "    #records = list that contains sequences split up by chromosome (and intrachromosome splits up to some size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['NC_000001.10 Homo sapiens chromosome 1, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000002.11 Homo sapiens chromosome 2, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000003.11 Homo sapiens chromosome 3, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000004.11 Homo sapiens chromosome 4, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000005.9 Homo sapiens chromosome 5, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000006.11 Homo sapiens chromosome 6, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000007.13 Homo sapiens chromosome 7, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000008.10 Homo sapiens chromosome 8, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000009.11 Homo sapiens chromosome 9, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000010.10 Homo sapiens chromosome 10, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000011.9 Homo sapiens chromosome 11, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000012.11 Homo sapiens chromosome 12, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000013.10 Homo sapiens chromosome 13, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000014.8 Homo sapiens chromosome 14, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000015.9 Homo sapiens chromosome 15, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000016.9 Homo sapiens chromosome 16, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000017.10 Homo sapiens chromosome 17, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000018.9 Homo sapiens chromosome 18, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000019.9 Homo sapiens chromosome 19, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000020.10 Homo sapiens chromosome 20, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000021.8 Homo sapiens chromosome 21, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000022.10 Homo sapiens chromosome 22, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000023.10 Homo sapiens chromosome X, GRCh37.p13 Primary Assembly',\n",
       " 'NC_000024.9 Homo sapiens chromosome Y, GRCh37.p13 Primary Assembly',\n",
       " 'NC_012920.1 Homo sapiens mitochondrion, complete genome']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#filtering out alternative sequences to only select consensus matches\n",
    "\n",
    "\n",
    "wrong = [\"alternate\", \"unplaced\", \"unlocalized\", \"patch\"]\n",
    "badlist = []\n",
    "for key in wrong:\n",
    "    for i in records:\n",
    "        ii = i.description\n",
    "        if key in ii:\n",
    "            badlist.append(ii)\n",
    "            \n",
    "filtered = []\n",
    "index_list = []\n",
    "for idx, i in enumerate(records):\n",
    "    ii = i.description\n",
    "    if ii not in badlist:\n",
    "        filtered.append(ii)\n",
    "        index_list.append(idx)\n",
    "        \n",
    "filtered\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SeqRecord(seq=Seq('NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN...NNN'), id='NC_000020.10', name='NC_000020.10', description='NC_000020.10 Homo sapiens chromosome 20, GRCh37.p13 Primary Assembly', dbxrefs=[])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chromosome = 20\n",
    "#22 (23-1) = X\n",
    "#23 (24-1) = Y\n",
    "#24 (25-1) = mitochondrial DNA\n",
    "records[index_list[chromosome-1]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading in gene coordinate information/annotation file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gene</th>\n",
       "      <th>gene_id</th>\n",
       "      <th>transcript_id</th>\n",
       "      <th>chrom</th>\n",
       "      <th>gene_start</th>\n",
       "      <th>gene_end</th>\n",
       "      <th>transcript_start</th>\n",
       "      <th>transcript_end</th>\n",
       "      <th>strand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABL1</td>\n",
       "      <td>ENSG00000097007.13</td>\n",
       "      <td>ENST00000318560.5</td>\n",
       "      <td>chr9</td>\n",
       "      <td>133589333</td>\n",
       "      <td>133763062</td>\n",
       "      <td>133710453</td>\n",
       "      <td>133763062</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AC004906.3</td>\n",
       "      <td>ENSG00000237286.1</td>\n",
       "      <td>ENST00000423194.1</td>\n",
       "      <td>chr7</td>\n",
       "      <td>2983669</td>\n",
       "      <td>2986725</td>\n",
       "      <td>2983669</td>\n",
       "      <td>2986725</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AC008738.1</td>\n",
       "      <td>ENSG00000230259.2</td>\n",
       "      <td>ENST00000425420.2</td>\n",
       "      <td>chr19</td>\n",
       "      <td>33790853</td>\n",
       "      <td>33793430</td>\n",
       "      <td>33790853</td>\n",
       "      <td>33793430</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACTG1</td>\n",
       "      <td>ENSG00000184009.5</td>\n",
       "      <td>ENST00000575842.1</td>\n",
       "      <td>chr17</td>\n",
       "      <td>79476997</td>\n",
       "      <td>79490873</td>\n",
       "      <td>79477015</td>\n",
       "      <td>79479807</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACVR1</td>\n",
       "      <td>ENSG00000115170.9</td>\n",
       "      <td>ENST00000263640.3</td>\n",
       "      <td>chr2</td>\n",
       "      <td>158592958</td>\n",
       "      <td>158732374</td>\n",
       "      <td>158592958</td>\n",
       "      <td>158731623</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>XRCC2</td>\n",
       "      <td>ENSG00000196584.2</td>\n",
       "      <td>ENST00000359321.1</td>\n",
       "      <td>chr7</td>\n",
       "      <td>152341864</td>\n",
       "      <td>152373250</td>\n",
       "      <td>152343589</td>\n",
       "      <td>152373250</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>YAP1</td>\n",
       "      <td>ENSG00000137693.9</td>\n",
       "      <td>ENST00000282441.5</td>\n",
       "      <td>chr11</td>\n",
       "      <td>101981192</td>\n",
       "      <td>102104154</td>\n",
       "      <td>101981192</td>\n",
       "      <td>102104154</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>YES1</td>\n",
       "      <td>ENSG00000176105.9</td>\n",
       "      <td>ENST00000314574.4</td>\n",
       "      <td>chr18</td>\n",
       "      <td>721588</td>\n",
       "      <td>812547</td>\n",
       "      <td>721748</td>\n",
       "      <td>812239</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>ZFHX3</td>\n",
       "      <td>ENSG00000140836.10</td>\n",
       "      <td>ENST00000268489.5</td>\n",
       "      <td>chr16</td>\n",
       "      <td>72816784</td>\n",
       "      <td>73093597</td>\n",
       "      <td>72816784</td>\n",
       "      <td>73082274</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>ZRSR2</td>\n",
       "      <td>ENSG00000169249.8</td>\n",
       "      <td>ENST00000307771.7</td>\n",
       "      <td>chrX</td>\n",
       "      <td>15808595</td>\n",
       "      <td>15841383</td>\n",
       "      <td>15808595</td>\n",
       "      <td>15841383</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>594 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           gene             gene_id      transcript_id  chrom  gene_start  \\\n",
       "0          ABL1  ENSG00000097007.13  ENST00000318560.5   chr9   133589333   \n",
       "1    AC004906.3   ENSG00000237286.1  ENST00000423194.1   chr7     2983669   \n",
       "2    AC008738.1   ENSG00000230259.2  ENST00000425420.2  chr19    33790853   \n",
       "3         ACTG1   ENSG00000184009.5  ENST00000575842.1  chr17    79476997   \n",
       "4         ACVR1   ENSG00000115170.9  ENST00000263640.3   chr2   158592958   \n",
       "..          ...                 ...                ...    ...         ...   \n",
       "589       XRCC2   ENSG00000196584.2  ENST00000359321.1   chr7   152341864   \n",
       "590        YAP1   ENSG00000137693.9  ENST00000282441.5  chr11   101981192   \n",
       "591        YES1   ENSG00000176105.9  ENST00000314574.4  chr18      721588   \n",
       "592       ZFHX3  ENSG00000140836.10  ENST00000268489.5  chr16    72816784   \n",
       "593       ZRSR2   ENSG00000169249.8  ENST00000307771.7   chrX    15808595   \n",
       "\n",
       "      gene_end  transcript_start  transcript_end strand  \n",
       "0    133763062         133710453       133763062      +  \n",
       "1      2986725           2983669         2986725      +  \n",
       "2     33793430          33790853        33793430      -  \n",
       "3     79490873          79477015        79479807      -  \n",
       "4    158732374         158592958       158731623      -  \n",
       "..         ...               ...             ...    ...  \n",
       "589  152373250         152343589       152373250      -  \n",
       "590  102104154         101981192       102104154      +  \n",
       "591     812547            721748          812239      -  \n",
       "592   73093597          72816784        73082274      -  \n",
       "593   15841383          15808595        15841383      +  \n",
       "\n",
       "[594 rows x 9 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filename1 = '/Users/samgould/Desktop/FSR Lab/2022-03-17/gene_info.csv'\n",
    "df1 = pd.read_csv(filename1)\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantifying the degree of coverage for CBE and ABE (using NG PAM)\n",
    "\n",
    "- should also look at collateral edits in window\n",
    "- also whether the edit falls within the canonical editing window (e.g. not at -1 relative to PAM)\n",
    "- base editing guidelines: https://benchling.com/pub/liu-base-editor\n",
    "\n",
    "## Generating the the boundaries of BE domains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "#changing it so that I look +/- 1 kb upstream and downstream of each gene to avoid issues with TERT mutations\n",
    "\n",
    "def BE_domains_boundaries(gene_name, df1):\n",
    "    \"Marks N in NGG pam sequence with a 1 in the zero array\"\n",
    "    #df1 is the dataframe containing gene sequence information\n",
    "\n",
    "    gene_chrom = df1[df1['gene']==gene_name]['chrom'].values[0]\n",
    "    \n",
    "    if gene_chrom != 'chrX':\n",
    "        chrom = int(re.search(r'\\d+', gene_chrom).group())\n",
    "    elif gene_chrom=='chrX':\n",
    "        chrom = 23 #it's number 22, but we subtract 1 below when accessing chromosome file\n",
    "        #there are no genes in this dataset that fall on Y chromosome -- ignoring\n",
    "\n",
    "    seq_start = df1[df1['gene']==gene_name]['gene_start'].values[0]\n",
    "    seq_end = df1[df1['gene']==gene_name]['gene_end'].values[0]\n",
    "\n",
    "    gene_sequence_1000eitherend = records[index_list[int(chrom)-1]].seq[seq_start-1001: seq_end+1000]\n",
    "    #gene sequence with 1000 bp buffer on either end to account for prime domains at beginning of gene\n",
    "\n",
    "    length_seq = len(gene_sequence_1000eitherend)\n",
    "\n",
    "    #two arrays corresponding to plus and minus end\n",
    "    zero_array_plus = np.zeros(length_seq)\n",
    "    zero_array_minus = np.zeros(length_seq)\n",
    "\n",
    "    #iterate through sequence\n",
    "\n",
    "    #iterate +- 1000 bp from start/end of gene\n",
    "    for idx, val in enumerate(gene_sequence_1000eitherend): \n",
    "        \n",
    "        by_twos = gene_sequence_1000eitherend[idx:idx+2]\n",
    "        by_twos_true = by_twos.upper()\n",
    "        \n",
    "        if by_twos_true == 'GG': #find NGGs\n",
    "            zero_array_plus[idx-1] += 1#add array of ones at appropriate index when NGG is encountered\n",
    "        \n",
    "        else:\n",
    "            continue\n",
    "\n",
    "\n",
    "    #repeat on negative strand\n",
    "    comp = gene_sequence_1000eitherend.complement() #taking complement (- strand in same orientation)\n",
    "    for idx, val in enumerate(comp):\n",
    "        \n",
    "        if idx+5 < length_seq: #dealing with boundary issue\n",
    "        \n",
    "            by_twos = comp[idx:idx+2]\n",
    "            by_twos_true = by_twos.upper() #make it upper case\n",
    "\n",
    "            if by_twos_true == 'GG': #find NGGs\n",
    "                zero_array_minus[idx+2] += 1#add array of ones at appropriate index when NGG is encountered\n",
    "                #+5 instead of +4 because we're counting from the back of the NGG due to orientation\n",
    "\n",
    "            else:\n",
    "                continue\n",
    "        \n",
    "        else:\n",
    "            continue\n",
    "    \n",
    "    #might be weird edge effects but I'm not using the very end of either of these arrays regardless...\n",
    "    \n",
    "    return [zero_array_plus,zero_array_minus]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5g/xxjcy2g531n02hnyb6d8qdsr0000gn/T/ipykernel_20629/1423816810.py:18: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
      "  np.save(filepath + 'BE_coverage_boundary_NGG_plusminus_1000bp' +'.npy', np.asarray(rt_len))\n"
     ]
    }
   ],
   "source": [
    "#repeating same process as above\n",
    "filename1 = '/Users/samgould/Desktop/FSR Lab/2022-03-17/gene_info.csv'\n",
    "df1 = pd.read_csv(filename1)\n",
    "\n",
    "unique_genes = np.unique(np.asarray(impact_data['Hugo_Symbol']))\n",
    "    \n",
    "rt_len = [] #coverage array for holding information\n",
    "\n",
    "for gene in unique_genes:\n",
    "\n",
    "    gene_name = gene\n",
    "\n",
    "    kkk = BE_domains_boundaries(gene_name, df1)\n",
    "\n",
    "    rt_len.append(kkk)\n",
    "        \n",
    "filepath = '/Users/samgould/Desktop/FSR Lab/2022-06-21/'\n",
    "np.save(filepath + 'BE_coverage_boundary_NGG_plusminus_1000bp' +'.npy', np.asarray(rt_len))\n",
    "\n",
    "#these files are provided in the drobox link...no need to run this yourself"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BE coverage classifier\n",
    "\n",
    "For CBE and ABE. CBE = C>T. ABE = A>G.\n",
    "\n",
    "CBE:\n",
    "- If mutation is C>T: look on plus strand for PAM\n",
    "- If mutation is G>A: look on minus strand for PAM\n",
    "\n",
    "ABE:\n",
    "- If mutation is A>G: look on plus strand for PAM\n",
    "- If mutations is T>C: look on minus strand for PAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "#need to fix df1 to include all hgvsc\n",
    "\n",
    "#TERT mutations and some others don't include this information for some reason...\n",
    "#issue with the MSK IMPACT dataset\n",
    "hgvsc_list = list(impact_data['HGVSc'])\n",
    "\n",
    "num_mutations = len(impact_data)\n",
    "for i in range(num_mutations):\n",
    "\n",
    "        #get info on current mut\n",
    "    mut = impact_data.iloc[i]\n",
    "        \n",
    "        #getting type of mutations\n",
    "    mut_type = mut['Variant_Type'] \n",
    "        \n",
    "    if mut_type == 'SNP': #can only edit snps\n",
    "        \n",
    "            #then checking what type of mutation it is\n",
    "        mut_transversion = impact_data.iloc[i]['HGVSc']\n",
    "            \n",
    "        if type(mut_transversion) != str:\n",
    "            #need to add inmissing HGVSc info\n",
    "            ref = mut['Reference_Allele']\n",
    "            a1 = mut['Tumor_Seq_Allele1']\n",
    "            a2 = mut['Tumor_Seq_Allele2']\n",
    "\n",
    "\n",
    "            if a1 != ref:\n",
    "                s1 = ref + '>' + a1\n",
    "                hgvsc_list[i] = s1\n",
    "\n",
    "            elif a2 != ref:\n",
    "                s1 = ref + '>' + a2\n",
    "                hgvsc_list[i] = s1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "impact_data['HGVSc']=hgvsc_list #replacing the old hgvsc list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "def BEcoverage_classifier(impact_data, df1):\n",
    "    #load in (1) impact_data, \n",
    "    #(2) df containing gene coordinate info\n",
    "    #(3) length of rt template\n",
    "    \n",
    "    filepath_boundary = '/Users/samgould/Desktop/FSR Lab/2022-06-21/BE_coverage_boundary_NGG_plusminus_1000bp.npy'\n",
    "    #this needs to be changed according to filepath\n",
    "\n",
    "    BE_domain_boundary = np.load(filepath_boundary, allow_pickle=True)#for plus and minus strand\n",
    "    \n",
    "    path = '/Volumes/Sam_G_SSD/human genome GrCh37 IMPACT genes/'\n",
    "    unique_genes = np.load(path + 'human_impact_genes_NAMES.npy', allow_pickle=True)\n",
    "    \n",
    "    #iterate through mutations in IMPACT dataset\n",
    "    num_mutations = len(impact_data)\n",
    "    \n",
    "    #initialize arrays of zeros for holding information about coverage\n",
    "    ABEproto = np.zeros(num_mutations)\n",
    "    ABEideal = np.zeros(num_mutations)\n",
    "    \n",
    "    CBEproto = np.zeros(num_mutations)\n",
    "    CBEideal = np.zeros(num_mutations)\n",
    "    \n",
    "    #initialize array for holding weird cases with bad location\n",
    "    outside_domain = []\n",
    "    snp_unrecorded = []\n",
    "    \n",
    "    for i in range(num_mutations):\n",
    "\n",
    "        #get info on current mut\n",
    "        mut = impact_data.iloc[i]\n",
    "        \n",
    "        #getting type of mutations\n",
    "        mut_type = mut['Variant_Type'] \n",
    "        \n",
    "        if mut_type == 'SNP': #can only edit snps\n",
    "        \n",
    "            #then checking what type of mutation it is\n",
    "            mut_transversion = impact_data.iloc[i]['HGVSc']\n",
    "            \n",
    "            if type(mut_transversion) != str: #check if the SNP is actually recorded\n",
    "                snp_unrecorded.append(i)                \n",
    "                \n",
    "                \n",
    "            else:\n",
    "\n",
    "                trans = mut_transversion[-3:]\n",
    "                t1 = ['C>T','G>A','A>G','T>C'] #mutations that can be encoded with CBE or ABE\n",
    "\n",
    "                if any(trans in t1 for k in t1):\n",
    "\n",
    "                    #getting gene and start/end position of mutation\n",
    "                    gene = mut['Hugo_Symbol']\n",
    "                    gene_index = list(unique_genes).index(gene) #retrieving index\n",
    "\n",
    "                    seq_start = df1[df1['gene']==gene]['gene_start'].values[0] \n",
    "\n",
    "                    s = mut['Start_Position']\n",
    "                    e = mut['End_Position']\n",
    "                    size_mut = (e-s)+1 #size of mutation\n",
    "\n",
    "                    #re-indexing with start of gene-1001 as position 0 (start of boundary array)\n",
    "                    start_true = s-(seq_start-1001)\n",
    "                    end_true = e-(seq_start-1001)+1\n",
    "             \n",
    "\n",
    "                    #retrieving the appropriate gene's prime editing domain\n",
    "                    BE_domain_bound = BE_domain_boundary[gene_index]\n",
    "                    \n",
    "\n",
    "                    #first checking for weird boundary misc.\n",
    "                    if (start_true or end_true)>len(BE_domain_bound[0]):\n",
    "                        outside_domain.append(i)\n",
    "                        print('gene_index: ' + str(gene_index))\n",
    "                        print(i)\n",
    "                        print(str(start_true) + ' ; ' +str(end_true) + '; len = ' + str(len(BE_domain_bound[0])))\n",
    "\n",
    "                    else:\n",
    "                        #first split into CBE and ABE\n",
    "                        CBE = ['C>T','G>A'] #mutations that can be encoded with CBE or ABE\n",
    "                        ABE = ['A>G','T>C'] \n",
    "                        \n",
    "                        if any(trans in CBE for k in CBE):\n",
    "\n",
    "                            if trans=='C>T':\n",
    "                                plus_end = BE_domain_bound[0] \n",
    "                                bound_proto = plus_end[start_true:start_true+21]\n",
    "                                bound_ideal = plus_end[start_true+13:start_true+18]\n",
    "                                \n",
    "                                if sum(bound_proto)>0:\n",
    "                                    CBEproto[i]+=1\n",
    "                                if sum(bound_ideal)>0:\n",
    "                                    CBEideal[i]+=1\n",
    "                                \n",
    "                            elif trans=='G>A':\n",
    "                                minus_end = BE_domain_bound[1] \n",
    "                                bound_proto = minus_end[start_true-21:start_true+1]\n",
    "                                bound_ideal = minus_end[start_true-17:start_true-12]\n",
    "                                \n",
    "                                if sum(bound_proto)>0:\n",
    "                                    CBEproto[i]+=1\n",
    "                                if sum(bound_ideal)>0:\n",
    "                                    CBEideal[i]+=1\n",
    "\n",
    "                                \n",
    "                        elif any(trans in ABE for k in ABE):\n",
    "                            \n",
    "                            if trans=='A>G':                                \n",
    "                                plus_end = BE_domain_bound[0] \n",
    "                                bound_proto = plus_end[start_true:start_true+21]\n",
    "                                bound_ideal = plus_end[start_true+13:start_true+18]\n",
    "                                \n",
    "                                if sum(bound_proto)>0:\n",
    "                                    ABEproto[i]+=1\n",
    "                                if sum(bound_ideal)>0:\n",
    "                                    ABEideal[i]+=1\n",
    "                                \n",
    "                            elif trans=='T>C':\n",
    "                                minus_end = BE_domain_bound[1] \n",
    "                                bound_proto = minus_end[start_true-21:start_true+1]\n",
    "                                bound_ideal = minus_end[start_true-17:start_true-12]\n",
    "                                \n",
    "                                if sum(bound_proto)>0:\n",
    "                                    ABEproto[i]+=1\n",
    "                                if sum(bound_ideal)>0:\n",
    "                                    ABEideal[i]+=1\n",
    "\n",
    "                        \n",
    "                else:\n",
    "                    continue\n",
    "                    \n",
    "        else: #can only edit SNPs\n",
    "            continue\n",
    "\n",
    "    return CBEproto,CBEideal,ABEproto, ABEideal, outside_domain, snp_unrecorded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "CBEproto,CBEideal,ABEproto, ABEideal, outside_domain, snp_unrecorded = BEcoverage_classifier(impact_data, df1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "#saving these arrays for later use\n",
    "filepath = '/Volumes/Sam_G_SSD/BE coverage quant NGG/'\n",
    "#np.save(filepath + 'CBE_proto.npy', CBEproto)\n",
    "#np.save(filepath + 'CBE_ideal.npy', CBEideal)\n",
    "#np.save(filepath + 'ABE_proto.npy', ABEproto)\n",
    "#np.save(filepath + 'ABE_ideal.npy', ABEideal)\n",
    "#np.save(filepath + 'snp_unrecorded.npy', snp_unrecorded)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figure Making\n",
    "\n",
    "This is the messy version with pertinent figures generated from the above analysis.\n",
    "\n",
    "The figures notebook collates all of this information into a single page. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SNP    348145\n",
       "DEL     49838\n",
       "INS     17784\n",
       "DNP      6042\n",
       "ONP      1011\n",
       "UNK         1\n",
       "TNP         1\n",
       "Name: Variant_Type, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mut_types= impact_data['Variant_Type'].value_counts()\n",
    "\n",
    "mut_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([82.3, 11.8,  4.2,  1.4,  0.2])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.asarray(np.round(100*(mut_types[:-2]/sum(mut_types[:-2])),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import rc\n",
    "rc('font',**{'family':'sans-serif','sans-serif':['Helvetica Neue']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bbox_props=dict(boxstyle='square,pad=0.3',fc ='w',ec='k',lw=0.72)\n",
    "kw=dict(xycoords='data',textcoords='data',arrowprops=dict(arrowstyle='-'),zorder=0,va='center')\n",
    "\n",
    "fig1,ax1=plt.subplots(figsize=(15,10))\n",
    "#labels=[\"first\\n1.8%\",\"second\\n1.3%\",\"third\\n10.5%\",\"fourth\\n13.8%\",\"fifth\\n7.8%\",\"sixth\\n6.7%\",\"seventh\\n9.9%\",\"eighth\\n12.2%\",\"ninth\\n12.7%\",\"tenth\\n10.9%\",\"eleventh\\n7.6%\",\"twelfth\\n4.8%\"]\n",
    "#values=[1.8,1.3,10.5,13.8,7.8,6.7,9.9,12.2,12.7,10.9,7.6,4.8]\n",
    "labels = np.asarray(impact_data['Variant_Type'].unique())\n",
    "perc = np.asarray(np.round(100*(mut_types[:-2]/sum(mut_types[:-2])),1))\n",
    "labels = [labels[i] + ' – ' + str(perc[i]) + '%' for i in range(len(perc))]\n",
    "values = mut_types[:-2]\n",
    "\n",
    "# Add code\n",
    "annotate_dict = {k:v for k,v in zip(labels, values)}\n",
    "val = [[x,y] for x,y in zip(sorted(values, reverse=True),sorted(values))]\n",
    "values1 = sum(val, [])\n",
    "\n",
    "new_labels = []\n",
    "for v in values1[:len(values)]:\n",
    "    for key, value in annotate_dict.items():\n",
    "        if v == value:\n",
    "            new_labels.append(key)\n",
    "c_list = [plt.cm.Blues(0.6), 'tab:orange',plt.cm.Purples(0.6),'tab:pink', 'tab:cyan']\n",
    "wedges,texts=ax1.pie(values1[:len(values)], explode=[0.1, 0.1, 0.1, 0.1,0.1],colors = c_list, labeldistance=.5,startangle=70)\n",
    "for i,p in enumerate(wedges):\n",
    "    ang=(p.theta2-p.theta1)/2. +p.theta1\n",
    "    y=np.sin(np.deg2rad(ang))\n",
    "    x=np.cos(np.deg2rad(ang))\n",
    "    horizontalalignment={-1:\"right\",1:\"left\"}[int(np.sign(x))]\n",
    "    connectionstyle=\"angle,angleA=0,angleB={}\".format(ang)\n",
    "    kw[\"arrowprops\"].update({\"connectionstyle\":connectionstyle})\n",
    "    ax1.annotate(new_labels[i],fontsize=18,xy=(x, y),xytext=(1.35*np.sign(x),1.4*y),\n",
    "                horizontalalignment=horizontalalignment,**kw)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "#plt.tight_layout()\n",
    "#fig1.savefig('mut_type_color_nolabels.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#SNP quantification\n",
    "snps = []\n",
    "unknown = []\n",
    "for i in range(len(impact_data)):\n",
    "    if impact_data.iloc[i]['Variant_Type']=='SNP':\n",
    "        mut_transversion = impact_data.iloc[i]['HGVSc']\n",
    "        if type(mut_transversion)==str:\n",
    "            trans = mut_transversion[-3:]\n",
    "            snps.append(trans)\n",
    "        else:\n",
    "            unknown.append(i)\n",
    "    else:\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['A>C', 'A>G', 'A>T', 'C>A', 'C>G', 'C>T', 'G>A', 'G>C', 'G>T',\n",
       "       'N>A', 'N>C', 'N>G', 'N>T', 'T>A', 'T>C', 'T>G'], dtype='<U3')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uniq,snp_count = np.unique(np.asarray(snps), return_counts=True)\n",
    "uniq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 7534, 21959, 10598, 18579, 15903, 86527, 92225, 19243, 42934,\n",
       "           4,     2,     6,    13,  8152, 11422,  7760])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snp_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "uniq_new = list(uniq[0:9]) + list(uniq[13:])\n",
    "snp_count_new = list(snp_count[0:9]) + list(snp_count[13:])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,8))\n",
    "a, b=[plt.cm.Blues, plt.cm.Purples]\n",
    "c_list = ['tab:grey', a(0.4),'tab:grey','tab:grey','tab:grey',b(0.4),b(0.4),'tab:grey',\n",
    "         'tab:grey','tab:grey',a(0.4),'tab:grey']\n",
    "plt.bar(uniq_new, 100*np.asarray(snp_count_new)/np.sum(np.asarray(snp_count_new)), color=c_list)\n",
    "plt.xticks(fontsize=16);\n",
    "plt.yticks(fontsize=18);\n",
    "plt.ylabel('Percentage of SNPs', fontsize=18);\n",
    "plt.xlabel('SNP', fontsize=18);\n",
    "#plt.savefig('SNP_breakdown.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = ['A>C\\nT>G', 'A>G\\nT>C', 'A>T\\nT>A', 'G>A\\nC>T', 'G>C\\nC>G', 'G>T\\nC>A']\n",
    "\n",
    "a = ['A>C', 'A>G', 'A>T', 'G>A', 'G>C', 'G>T']\n",
    "b = ['T>G', 'T>C', 'T>A', 'C>T', 'C>G', 'C>A']\n",
    "compact = []\n",
    "for i in range(len(a)):\n",
    "    a1 = uniq_new.index(a[i])\n",
    "    b1 = uniq_new.index(b[i])\n",
    "    add = snp_count_new[a1] + snp_count_new[b1]\n",
    "    compact.append(add)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[15294, 33381, 18750, 178752, 35146, 61513]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,8))\n",
    "a, b=[plt.cm.Blues, plt.cm.Purples]\n",
    "c_list = ['tab:grey', a(0.4),'tab:grey',b(0.4),'tab:grey','tab:grey']\n",
    "plt.bar(labels, 100*np.asarray(compact)/np.sum(np.asarray(compact)), color=c_list)\n",
    "plt.xticks(fontsize=16);\n",
    "plt.yticks(fontsize=18);\n",
    "plt.ylabel('Percentage of SNPs', fontsize=18);\n",
    "plt.xlabel('SNP', fontsize=18);\n",
    "\n",
    "perc = 100*np.asarray(compact)/np.sum(np.asarray(compact))\n",
    "\n",
    "for i in range(6):\n",
    "    plt.text(i, perc[i]+0.5, str(np.round(perc[i], 1)) + '%', ha = 'center', fontsize=15)\n",
    " \n",
    "plt.savefig('SNP_breakdown2.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10598"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snp_count[list(uniq).index('A>T')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "348145"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(snp_count) + len(unknown)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make data: I have 3 groups and 7 subgroups\n",
    "group_names=['SNP', 'other mutation \\n        type'] #\n",
    "snp_unrecorded=unknown\n",
    "group_size=[mut_types[0]-len(snp_unrecorded), sum(mut_types)-mut_types[0]-len(snp_unrecorded)] #excluding missing SNPs\n",
    "subgroup_names=['A>G', 'T>C','C>T', 'G>A', 'non-editable']\n",
    "sum1 = snp_count[list(uniq).index('A>G')]+snp_count[list(uniq).index('T>C')]+snp_count[list(uniq).index('C>T')]+snp_count[list(uniq).index('G>A')]\n",
    "subgroup_size = [snp_count[list(uniq).index('A>G')],snp_count[list(uniq).index('T>C')],snp_count[list(uniq).index('C>T')],snp_count[list(uniq).index('G>A')], sum(mut_types)-sum1-len(snp_unrecorded)]\n",
    "#subgroup_size=[4,3,5,6,5,10,5,5,4,6]\n",
    " \n",
    "# Create colors\n",
    "a, b, c, d=[plt.cm.Blues, plt.cm.Reds, plt.cm.Greens, plt.cm.Purples]\n",
    " \n",
    "# First Ring (outside)\n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "ax.axis('equal')\n",
    "mypie, _ = ax.pie(group_size, radius=1.3, labels=group_names, colors=[a(0.6), b(0.6), c(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie, width=0.3, edgecolor='white')\n",
    " \n",
    "# Second Ring (Inside)\n",
    "mypie2, _ = ax.pie(subgroup_size, radius=1.3-0.3, labels=subgroup_names, labeldistance=0.7, colors=[c(0.6), c(0.4), d(0.6), d(0.4), b(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie2, width=0.4, edgecolor='white')\n",
    "plt.margins(0,0)\n",
    " \n",
    "# show it\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "#fig.savefig('access.png', dpi=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#loading in coverage information\n",
    "filepath = '/Volumes/Sam_G_SSD/BE coverage quant NGG/'\n",
    "CBEproto = np.load(filepath + 'CBE_proto.npy')\n",
    "CBEideal = np.load(filepath + 'CBE_ideal.npy')\n",
    "ABEproto = np.load(filepath + 'ABE_proto.npy')\n",
    "ABEideal = np.load(filepath + 'ABE_ideal.npy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cprot = sum(CBEproto)/ (len(impact_data))\n",
    "\n",
    "\n",
    "labels1 = ['CBE proto', '']\n",
    "labels2 = ['CBE ideal', '']\n",
    "labels3 = ['ABE proto', '']\n",
    "labels4 = ['ABE ideal', '']\n",
    "labels5 = ['CBE or ABE proto', '']\n",
    "labels6 = ['CBE or ABE ideal', '']\n",
    "\n",
    "sizes1 = [sum(CBEproto), (len(impact_data))-sum(CBEproto)]\n",
    "sizes2 = [sum(CBEideal), (len(impact_data))-sum(CBEideal)]\n",
    "sizes3 = [sum(ABEproto), (len(impact_data))-sum(ABEproto)]\n",
    "sizes4 = [sum(ABEideal), (len(impact_data))-sum(ABEideal)]\n",
    "sizes5 = [sum(ABEproto)+sum(CBEproto), (len(impact_data))-(sum(ABEproto)+sum(CBEproto))]\n",
    "sizes6 = [sum(ABEideal)+sum(CBEideal), (len(impact_data))-(sum(ABEideal)+sum(CBEideal))]\n",
    "\n",
    "\n",
    "\n",
    "explode = (0.1, 0.1)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(3, 2, figsize=(10,10))\n",
    "ax1[0][0].set_title('Percentage of all MSK IMPACT mutations accessible', fontsize=15)\n",
    "\n",
    "\n",
    "ax1[0][0].pie(sizes1, explode=explode, labels=labels1, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[0][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[0][1].pie(sizes2, explode=explode, labels=labels2, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[0][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[1][0].pie(sizes3, explode=explode, labels=labels3, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[1][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[1][1].pie(sizes4, explode=explode, labels=labels4, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[1][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[2][0].pie(sizes5, explode=explode, labels=labels5, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[2][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[2][1].pie(sizes6, explode=explode, labels=labels6, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[2][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "#fig1.savefig('Pie_mutation_rep.png', dpi=200)\n",
    "#fig1.savefig('allMuts_accessibleTERTincl.png', dpi=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "labels1 = ['CBE proto', '']\n",
    "labels2 = ['CBE ideal', '']\n",
    "labels3 = ['ABE proto', '']\n",
    "labels4 = ['ABE ideal', '']\n",
    "labels5 = ['CBE or ABE proto', '']\n",
    "labels6 = ['CBE or ABE ideal', '']\n",
    "\n",
    "sizes1 = [sum(CBEproto), ((mut_types[0]))-sum(CBEproto)]\n",
    "sizes2 = [sum(CBEideal), ((mut_types[0]))-sum(CBEideal)]\n",
    "sizes3 = [sum(ABEproto), ((mut_types[0]))-sum(ABEproto)]\n",
    "sizes4 = [sum(ABEideal), ((mut_types[0]))-sum(ABEideal)]\n",
    "sizes5 = [sum(ABEproto)+sum(CBEproto), ((mut_types[0]))-(sum(ABEproto)+sum(CBEproto))]\n",
    "sizes6 = [sum(ABEideal)+sum(CBEideal), ((mut_types[0]))-(sum(ABEideal)+sum(CBEideal))]\n",
    "\n",
    "\n",
    "\n",
    "explode = (0.1, 0.1)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(3, 2, figsize=(10,10))\n",
    "\n",
    "ax1[0][0].set_title('Percentage of all MSK IMPACT SNPs accessible', fontsize=15)\n",
    "\n",
    "\n",
    "\n",
    "ax1[0][0].pie(sizes1, explode=explode, labels=labels1, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[0][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[0][1].pie(sizes2, explode=explode, labels=labels2, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[0][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[1][0].pie(sizes3, explode=explode, labels=labels3, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[1][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[1][1].pie(sizes4, explode=explode, labels=labels4, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[1][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[2][0].pie(sizes5, explode=explode, labels=labels5, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[2][0].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1[2][1].pie(sizes6, explode=explode, labels=labels6, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1[2][1].axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "#fig1.savefig('SNPs_accessibleTERTincl.png', dpi=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loading in coverage information\n",
    "filepath = '/Volumes/Sam_G_SSD/BE coverage quant NGG/'\n",
    "CBEproto = np.load(filepath + 'CBE_proto.npy')\n",
    "CBEideal = np.load(filepath + 'CBE_ideal.npy')\n",
    "ABEproto = np.load(filepath + 'ABE_proto.npy')\n",
    "ABEideal = np.load(filepath + 'ABE_ideal.npy')\n",
    "\n",
    "# Make data: I have 3 groups and 7 subgroups\n",
    "group_names=['SNP – 82.3%', 'Other mutation \\n type – 17.7%'] #\n",
    "#group_names=['', '']\n",
    "snp_unrecorded = []\n",
    "group_size=[mut_types[0]-len(snp_unrecorded), sum(mut_types)-mut_types[0]-len(snp_unrecorded)] #excluding missing SNPs\n",
    "subgroup_names=['CBE high', 'CBE low', 'ABE high', 'ABE low', '']\n",
    "#subgroup_names=['', '', '', '', '']\n",
    "\n",
    "subgroup_size = [sum(CBEideal), sum(CBEproto)-sum(CBEideal), sum(ABEideal), sum(ABEproto)-sum(ABEideal), sum(mut_types)-sum(CBEproto)-sum(ABEproto)-len(snp_unrecorded)]\n",
    "#subgroup_size=[4,3,5,6,5,10,5,5,4,6]\n",
    " \n",
    "# Create colors\n",
    "a, b, c, d=[plt.cm.Blues, plt.cm.Reds, plt.cm.Greens, plt.cm.Purples]\n",
    " \n",
    "# First Ring (outside)\n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "ax.axis('equal')\n",
    "mypie, _ = ax.pie(group_size, radius=1.3, labels=group_names, colors=[a(0.6), 'tab:gray', c(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie, width=0.3, edgecolor='white')\n",
    " \n",
    "# Second Ring (Inside)\n",
    "mypie2, _ = ax.pie(subgroup_size, radius=1.3-0.3, labels=subgroup_names, labeldistance=0.68, colors=[d(0.4), d(0.2), a(0.4), a(0.2), b(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie2, width=0.4, edgecolor='white')\n",
    "plt.margins(0,0)\n",
    " \n",
    "# show it\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "#fig.savefig('BE_donut_human_NGG_nolabels.png', dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make data: I have 3 groups and 7 subgroups\n",
    "group_names=['SNP – 82.3%', 'Other mutation \\n type – 17.7%'] #\n",
    "snp_unrecorded = []\n",
    "group_size=[mut_types[0]-len(snp_unrecorded), sum(mut_types)-mut_types[0]-len(snp_unrecorded)] #excluding missing SNPs\n",
    "subgroup_names=['CBE ideal', 'CBE proto', 'ABE ideal', 'ABE proto', 'non-editable']\n",
    "\n",
    "subgroup_size = [sum(CBEideal), sum(CBEproto)-sum(CBEideal), sum(ABEideal), sum(ABEproto)-sum(ABEideal), sum(mut_types)-sum(CBEproto)-sum(ABEproto)-len(snp_unrecorded)]\n",
    "#subgroup_size=[4,3,5,6,5,10,5,5,4,6]\n",
    " \n",
    "# Create colors\n",
    "a, b, c, d=[plt.cm.Blues, plt.cm.Reds, plt.cm.Greens, plt.cm.Purples]\n",
    " \n",
    "# First Ring (outside)\n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "ax.axis('equal')\n",
    "mypie, _ = ax.pie(group_size, radius=1.3, labels=group_names, colors=[a(0.6), 'tab:gray', c(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie, width=0.3, edgecolor='white')\n",
    " \n",
    "# Second Ring (Inside)\n",
    "mypie2, _ = ax.pie(subgroup_size, radius=1.3-0.3, labels=subgroup_names, labeldistance=0.7, colors=[d(0.6), d(0.4), c(0.6), c(0.4), b(0.6)], textprops={'fontsize': 15})\n",
    "plt.setp( mypie2, width=0.4, edgecolor='white')\n",
    "plt.margins(0,0)\n",
    " \n",
    "# show it\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "#fig.savefig('donut_plot.png', dpi=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
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   "window_display": false
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 },
 "nbformat": 4,
 "nbformat_minor": 4
}
